Abstract
Assessment of a low skeletal muscle mass (SM) is important for diagnosis of ageing and disease-associated sarcopenia and is hindered by heterogeneous methods and terminologies that lead to differences in diagnostic criteria among studies and even among consensus definitions. The aim of this review was to analyze and summarize previously published cut-offs for SM applied in clinical and research settings and to facilitate comparison of results between studies. Multiple published reference values for discrepant parameters of SM were identified from 64 studies and the underlying methodological assumptions and limitations are compared including different concepts for normalization of SM for body size and fat mass (FM). Single computed tomography or magnetic resonance imaging images and appendicular lean soft tissue by dual X-ray absorptiometry (DXA) or bioelectrical impedance analysis (BIA) are taken as a valid substitute of total SM because they show a high correlation with results from whole body imaging in cross-sectional and longitudinal analyses. However, the random error of these methods limits the applicability of these substitutes in the assessment of individual cases and together with the systematic error limits the accurate detection of changes in SM. Adverse effects of obesity on muscle quality and function may lead to an underestimation of sarcopenia in obesity and may justify normalization of SM for FM. In conclusion, results for SM can only be compared with reference values using the same method, BIA- or DXA-device and an appropriate reference population. Limitations of proxies for total SM as well as normalization of SM for FM are important content-related issues that need to be considered in longitudinal studies, populations with obesity or older subjects.
Highlights
Beyond the well-established role of ageing associated loss in skeletal muscle mass (SM) as a risk factor of frailty, morbidity and mortality in older people, a low SM is observed as a result of diseases like malignant cancer, chronic obstructive pulmonary disease, heart failure and Nutrients 2020, 12, 755; doi:10.3390/nu12030755 www.mdpi.com/journal/nutrientsNutrients 2020, 12, 755 renal failure and is an emerging prognostic marker in a number of diseases [2–12]
Published cut-off points for a low SM normalized by height are presented in Tables 1–3 stratified by dual X-ray absorptiometry (DXA), bioelectrical impedance analysis (BIA) and computed tomography (CT)
In the majority of studies (14 of 32), SM was measured by DXA using lean soft tissue from the arms and legs normalized by height2 given as appendicular skeletal muscle mass index (ASMI) [22,38–50]
Summary
Beyond the well-established role of ageing associated loss in skeletal muscle mass (SM) (primary sarcopenia) as a risk factor of frailty, morbidity and mortality in older people, a low SM is observed as a result of diseases like malignant cancer, chronic obstructive pulmonary disease, heart failure and Nutrients 2020, 12, 755; doi:10.3390/nu12030755 www.mdpi.com/journal/nutrientsNutrients 2020, 12, 755 renal failure (secondary sarcopenia [1]) and is an emerging prognostic marker in a number of diseases [2–12]. The assessment of SM by segmentation of continuous whole body magnetic resonance imaging (MRI) is considered as the gold standard [17]. This method is too cumbersome and expensive for clinical practice and is even rarely used in studies with larger sample sizes [17,18]. Dual X-ray absorptiometry (DXA) is used to assess appendicular lean soft tissue (ASM, the sum of lean soft tissue from both arms and legs) or fat-free mass (FFM, total lean soft tissue plus bone mineral mass or body weight minus FM) as a proxy for SM. More simple and even non-invasive, the output of bioelectrical impedance analysis (BIA) depends on the reference method used to generate the BIA algorithm and can be FFM [20], ASM, e.g., [21–23] or even SM, e.g., [24–27]
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